MATLAB-based Methods Allow Precise, High-Throughput Quantification of Nuclear Morphology and Texture in Tachycardiomyopathy.

Abstract

The understanding of cardiomyopathies is hindered by a lack of quantitative histologic data. To address this methodical gap, we wrote a MATLAB-based image analysis platform to quantify nuclear and cellular disarray. We validated its utility in an animal model of tachycardiomyopathy (T-CM), whose ultrastructural remodeling processes have only partially been characterized and differ substantially from more prevalent cardiomyopathies. Six rabbits received right ventricular pacemaker implants. Three animals were paced incrementally up to 380 bpm for 30 days to induce T-CM. In three control rabbits, the pacemaker remained inactive (SHAM). Left ventricular tissue was collected, fixed in formalin, embedded in paraffin, stained, and digitized for nuclear morphometry, texture analysis, orientation analysis, and vascular architecture evaluation. Nuclear segmentation performed by the software was highly accurate, closely matching manual counts (mean manual nuclear count per slide = 81.3 ± 3.8, mean automated nuclear count per slide = 81.9 ± 4.3, r = 0.981, p<0.001). In T-CM, nuclei were enlarged [SHAM (a.u.) = 2362, T-CM (a.u.) = 2660, p=0.0042]. Texture patterns differed between the groups with higher nuclear contrast in T-CM [SHAM (a.u.) = 0.0169, T-CM (a.u.) = 0.0247, p=0.0149], highlighting structural remodeling at the nuclear level. Median vessel size increased in T-CM [SHAM (a.u.) = 1532, T-CM (a.u.) = 2421, p<0.0001]. In conclusion, our MATLAB-based image analysis platform allows high-throughput quantification of nuclear and extracellular disarray. It identified enlargement of nuclei and increased nuclear contrast as part of ultrastructural remodeling in tachycardiomyopathy.